Tarabichi, Saad

Abstract Purpose The diagnostic accuracy of imaging modalities in periprosthetic joint infections (PJIs) remains uncertain. This study assessed and compared the performance of different imaging techniques for diagnosing PJI. Methods A systematic review and meta‐analysis of studies published in PubMed and Embase (1 January 2000 to 1 March 2024) was conducted. Eligible studies included adults (≥18 years), applied a valid reference standard for PJI diagnosis, and provided sufficient data to construct 2 × 2 contingency tables. Imaging modalities included white blood cell scintigraphy (WBCS), FDG‐PET/CT, antigranulocyte scintigraphy (AGS), bone scintigraphy (BS), magnetic resonance imaging (MRI), computed tomography (CT) and related combinations. Risk of bias was assessed using the QUADAS‐2 tool. A bivariate random‐effects model estimated pooled diagnostic odds ratios, sensitivities, and specificities with 95% confidence intervals (CIs). Results Forty studies (1263 PJI cases, 4700 controls) were included. Pooled sensitivity and specificity were as follows: WBCS‐SPECT/CT: 87.1% (95% CI, 31.7–99.0) and 94.1% (95% CI, 87.5–97.3); WBCS‐BMS: 79.7% (95% CI, 58.3–91.7) and 94.2% (95% CI, 91.0–96.3); WBCS: 88.1% (95% CI, 73.8–95.1) and 80.0% (95% CI, 62.2–90.7); FDG‐PET (±PET/CT): 88.1% (95% CI, 79.9–93.2) and 87.2% (95% CI, 76.3–93.5); BS‐WBCS: 59.5% (95% CI, 43.2–73.9) and 96.6% (95% CI, 92.2–98.6); BS: 89.3% (95% CI, 80.9–94.2) and 74.1% (95% CI, 59.0–85.0); AGS: 89.1% (95% CI, 76.8–95.3) and 73.0% (95% CI, 63.1–81.0). No eligible studies were identified for MRI or CT. Substantial heterogeneity was observed. Conclusion Diagnostic performance varied substantially, and no modality consistently demonstrated superior accuracy. WBCS showed the most stable results, particularly when combined with BS or BMS. Given the heterogeneity and variability in specificity, imaging should complement comprehensive diagnostic evaluation rather than be used in isolation. Level of Evidence 2a–3a, systematic review and meta‐analysis of retrospective cohort and case‐control studies.

Background The diagnosis of periprosthetic joint infection (PJI) is facilitated by consensus identification of synovial biomarkers, which may be aided by targeted microbial next generation sequencing (NGS) of synovial fluid. The primary objective of the study was to evaluate NGS performance across 3 years to ICM 2018 minor criteria for PJI. Methods Synovial fluid specimens submitted from 2020–2022 by outpatient surgical clinics to MicroGenDX for matched synovial biomarker and NGS analysis were selected for retrospective analysis. Synovial biomarkers tested included C-reactive protein (CRP), white blood cell (WBC) count, and polymorphonuclear (PMN) leukocyte percentage. Synovial fluid analysis compared NGS microbial positivity with positive incidence of PJI determined by scoring of synovial biomarkers using ICM 2018 minor criteria for infection. Results The overall sensitivity, specificity, and accuracy of NGS to ICM diagnosed PJI across 2,011 specimens was 76.4% [95% CI, 0.723–0.801], 92.3% [0.91–0.94], and 88.7% [0.87–0.90], respectively. When comparing the diagnostic performance of NGS and individual biomarkers to infection, NGS was more specific to PJI than synovial CRP (specificity = 0.894, 95% CI: 0.88–0.91), but not PMN or WBC. NGS was positive in 7.7% of ICM negative samples. NGS positive: ICM negative samples were associated with significantly elevated synovial PMN ( p = 0.001) and WBC ( p < 0.0001) compared to NGS negative: ICM negative samples. Across all samples, NGS positivity was associated with significantly elevated results for all tested biomarkers ( p < 0.0001). Eight bacterial species dominated the composition in 68% of samples, whereas 46 different microbes were dominant in the remaining third. Conclusion Microbial targeted NGS positivity was concordant with ICM minor criteria for PJI and should be considered a useful tool for diagnosis. There is a low risk of false positive detections comparable to ICM biomarkers. Elevated biomarkers in NGS positive: ICM negative samples may indicate infection occurring that is poorly captured by the three measured synovial biomarkers. Uncommon species are collectively common to PJI and NGS is uniquely positioned to detect such species as they are frequently missed by conventional microbiological testing, including culture and quantitative PCR. These results suggest formal diagnostic schemes would benefit from the addition of NGS as a diagnostic criterion.

Purpose To assess the ability of artificial intelligence (AI) to identify common sports‐related pathologies using radiologic imaging and to compare ChatGPT 4.0 with 2 competitors, Grok 2 and Claude 3.5 Sonnet. Methods ChatGPT 4.0, Grok 2, and Claude 3.5 Sonnet were used. Five common orthopaedic sports pathologies were chosen: anterior cruciate ligament tears, posterior cruciate ligament tears, meniscal tears, chondral pathologies, and rotator cuff tears. Fifty images representing each pathology were collected from a radiologic imaging database when possible, which included radiographic images, computed tomography, and magnetic resonance imaging. Normal images were collected that corresponded to each diagnostic category. Receiver operator characteristic curves and area under the curve values were calculated to assess the accuracy of each AI platform. Results ChatGPT 4.0, Grok 2, and Claude 3.5 Sonnet accurately identified the pathology in 23.6%, 15.7%, and 17.1% of diseased images, respectively. ChatGPT and Grok were most accurate at identifying meniscus pathologies (ChatGPT: 48%, Grok: 42%), whereas Claude Sonnet was most accurate at identifying anterior cruciate ligament pathologies (30%). The area under the curve for ChatGPT, Grok, and Claude Sonnet was 0.21, 0.16, and 0.15, respectively (ChatGPT 4.0 vs Grok 2, P = .30; ChatGPT 4.0 vs Claude 3.5 Sonnet, P = .24; Grok 2 vs Claude 3.5 Sonnet, P > .99). There were no differences in performance between the 3 platforms overall or within any of the diagnostic categories. Conclusions ChatGPT 4.0, Grok 2, and Claude 3.5 Sonnet correctly identified the pathology in less than 25% of images of common sports‐related pathologies and showed area under the curve values well below 0.5, indicating poor accuracy. Based on these findings, we do not recommend the current use of these generative AI models for image‐based diagnosis in orthopaedics. Clinical Relevance As the use of AI becomes more popular within the general public, it becomes increasingly important to make aware the capabilities and limitations of popular AI platforms in regard to their current image‐based diagnostic capabilities.

Background Robotic-assisted TKA may allow for more reproducible balancing and implant positioning. However, few RCTs have directly compared modern robotic-assisted TKA to conventional TKA. Questions/purposes (1) Do patients undergoing robotic-assisted TKA perform better on the Timed Up and Go (TUG) test and Stair Climb test (SCT) than patients undergoing conventional TKA at 1 and 6 months after surgery? (2) Do patients undergoing robotic-assisted TKA demonstrate better patient-reported outcomes, including Knee Injury and Osteoarthritis Outcome Score (KOOS), EQ-5D, and VAS scores, than patients undergoing conventional TKA at 1 and 6 months after surgery? (3) Do patients undergoing robotic-assisted TKA demonstrate better radiographic alignment and position than patients undergoing conventional TKA? Methods In this double-blind RCT, 60 patients were randomized to robotic-assisted TKA (n = 30) or conventional TKA (n = 30) without the use of a tensioning device. All care was otherwise standardized, using mechanical alignment guides. The primary outcome measures were the TUG and SCT tests; results were collected by a blinded observer at 6 months postoperatively. These time points were chosen based on the maximal early improvement in patient-reported outcomes and bimodal distribution of the TUG and SCT tests, worsening in the immediate postoperative period, and improving within the first 6 months. Secondary outcome measures were KOOS, EQ-5D, and VAS scores; radiographic measurements; and operative time. Standard bivariate statistical analysis was conducted. The mean ± SD age of the cohort was 66 ± 7 years, with no differences between groups (p = 0.21). Ninety-three percent (28 of 30) of patients in the robotic-assisted group were White versus 97% (29 of 30) in the conventional TKA group (p > 0.99). Women made up 57% (17) of the robotic-assisted cohort and 60% (18) of the conventional TKA cohort. No differences were noted between the robotic-assisted and conventional TKA groups in BMI, Charlson comorbidity index, or American Society of Anesthesiologists (ASA) classification. Results Patients undergoing robotic-assisted TKA did not perform better than those who underwent conventional TKA on the TUG (11 versus 11 seconds; p = 0.88) or SCT (15 versus 15 seconds; p = 0.93) tests. Patients undergoing robotic-assisted TKA did not demonstrate better mean ± SD scores on the KOOS pain subscale than patients undergoing conventional TKA (86 ± 14 versus 80 ± 17; p = 0.15). Patients undergoing robotic-assisted TKA did not demonstrate better radiographic alignment and position than patients undergoing conventional TKA based on hip-knee-ankle angle (178° versus 178°; p = 0.89). No differences between the two groups were noted at the 1-month follow-up in TUG and SCT test results. Conclusion In this study, patients who underwent robotically assisted TKA did no better in terms of function, patient-reported outcomes, or radiographic measures than did patients who underwent conventional TKA. Until or unless future studies demonstrate benefits of robotically assisted TKA that are large enough for patients to perceive, we recommend against its use. Level of Evidence Level I, therapeutic study.

Introduction: Total knee arthroplasty (TKA) is a widely performed elective procedure globally. Periprosthetic joint infection (PJI) remains a serious complication following TKA. Hematogenous seeding from distant infections is a recognized mechanism of PJI. However, to our knowledge, there are no published reports of hematogenous PJI originating from acute epididymo-orchitis. Case Report: A 74-year-old male presented to the emergency department following a ground-level fall on his right knee. He was diagnosed with a knee effusion and discharged for outpatient follow-up. Approximately one week later, the patient presented to his primary care physician with right scrotal swelling and was diagnosed with epididymitis and started on oral antibiotics. The following day, he underwent right knee arthrocentesis which was positive for an acute PJI. The patient then underwent a double debridement, antibiotics and implant retention (DAIR) procedure and was discharged on a six-month course of oral antibiotics. Eight months after the double DAIR, the patient developed right knee swelling and erythema. Right knee aspiration was positive for a persistent PJI, and the patient underwent resection arthroplasty with insertion of an antibiotic spacer. Conclusion: Hematogenous spread of epididymoorchitis resulting in PJI is a rare and underreported complication that has not been fully understood in the literature. In this case, several risk factors—such as the presence of a prosthetic joint, recent trauma, and chronic corticosteroid use—may have increased the patient’s susceptibility to infection. Close monitoring of inflammatory markers such as C-reactive protein, erythrocyte sedimentation rate, and white blood cell count can aid in the early detection of septic arthritis and contribute to improved patient outcomes.

Background: Although it is well established that the type of organism can be a risk factor for failure in patients with periprosthetic joint infection (PJI), no study to date has examined the impact of the number of positive cultures on treatment outcomes in patients undergoing 2-stage exchange. The purpose of this multicenter study was to determine the prognostic utility of multiple positive cultures at resection as a predictor of failure following reimplantation. Methods: This retrospective multicenter study identified 437 patients with chronic knee PJI who had undergone 2-stage exchange arthroplasty with a minimum of 1 year of follow-up following reimplantation. PJI was defined with use of the 2013 Musculoskeletal Infection Society (MSIS) criteria. Patients with culture-negative PJI were excluded (n = 138). Treatment failure was defined as either any reoperation for infection or PJI-related mortality. Multivariable regression controlling for risk factors for failure after a 2-stage arthroplasty was performed to determine whether ≥2 positive intraoperative cultures at resection can predict outcomes following reimplantation when compared with a single positive culture. Results: Two hundred and ninety-nine patients were included. At a mean follow-up of 6.2 ± 2.6 years, 48 patients (16.1%) experienced failure. Patients who had a failure were more likely to have had a longer interstage interval (p = 0.038) and were also more likely to have had ≥2 positive cultures at the time of resection arthroplasty (95.8% versus 75.3%; p = 0.001). On regression analysis, ≥2 positive cultures at resection was the only variable that was identified as a risk factor for failure following reimplantation in both the univariate (odds ratio [OR], 7.55 [95% CI, 2.24 to 47.0]; p = 0.006) and multivariable models (OR, 8.12 [95% CI, 2.31 to 51.9]; p = 0.005). Conclusions: This is the first study to examine the impact of the number of positive cultures on outcomes in patients with PJI. We found that the presence of ≥2 positive cultures at resection was an indicator of a poor prognosis and resulted in a greater than eightfold increase in the risk of treatment failure in patients undergoing a 2-stage exchange. Level of Evidence: Prognostic Level III . See Instructions for Authors for a complete description of levels of evidence.

AimThis study aimed to evaluate the impact of intraoperative direct sonication on the yield of traditional culture and the time to positivity (TTP) of cultures obtained for periprosthetic joint infection (PJI), thereby assessing its potential to improve diagnostic efficiency and reduce contamination risk.MethodA prospective cohort study was conducted at a tertiary care center, involving 190 patients undergoing revision surgery for PJI from August 2021 to January 2024. Patients were included based on the 2018 International Consensus Meeting definition of PJI. The study utilized a novel sonication protocol, which involved direct intraoperative sonication of the implant and tissue, followed by incubation in a BACT/ALERT 3D system. The primary outcomes measured were the number and percentage of positive culture samples, identified microorganisms, and the TTP of each culture. Statistical analysis was performed using R software, with various tests applied to assess the significance of findings.ResultsThe study included 510 positive cultures from 190 patients, demonstrating that sonication significantly improved the positivity rate for both tissue and prosthesis specimens (p < 0.05). The median TTP for all samples was 3.13 days, with sonicated samples showing a significantly shorter TTP compared to non-sonicated samples (p < 0.05). Specifically, the shortest median TTP was observed in prosthesis post-sonication samples. Furthermore, the study found that Gram-positive organisms had a shorter TTP than gram-negative organisms, and specific microorganisms like Staphylococcus aureus and MRSE showed the fastest TTP. The analysis also revealed higher positivity rates in chronic PJIs compared to acute PJIs for sonicated tissue samples.ConclusionsThe study demonstrates that intraoperative direct sonication combined with the BACT/ALERT 3D system can significantly enhance the diagnostic yield of cultures and reduce the TTP for common PJI pathogens. This novel technique not only improves pathogen detection, facilitating the tailoring of antibiotic therapy, but also potentially reduces the risk of contamination associated with sonication. These findings suggest that direct intraoperative sonication could be a valuable addition to the current diagnostic protocols for PJI, contributing to more effective management and treatment of this complex condition. Further research is necessary to explore the clinical significance of TTP and its correlation with patient outcomes in PJI.